Soft computing is likely to play an important role in science and engineering in the future. The successful applications of soft computing and the rapid growth suggest that the impact of soft computing will be felt increasingly in coming years. Soft Computing encourages the integration of soft computing techniques and tools into both everyday and advanced applications. This Open access peer-reviewed journal serves as a platform that fosters new applications for all scientists and engineers engaged in research and development in this fast growing field.

1. June 2020: Most Downloaded
Article in Soft Computing
International Journal on Soft Computing ( IJSC )
ISSN: 2229 - 6735 [Online] ; 2229 - 7103 [Print]
http://airccse.org/journal/ijsc/ijsc.html

2. DETERMINATION OF OVER-LEARNING AND OVER-FITTING PROBLEM IN
BACK PROPAGATION NEURAL NETWORK
Gaurang Panchal1
, Amit Ganatra2
, Parth Shah3
, Devyani Panchal4
Department of Computer Engineering, Charotar Institute of Technology (Faculty of
Technology and Engineering), Charotar University of Science and Technology,
Changa, Anand-388 421, INDIA
ABSTRACT
A drawback of the error-back propagation algorithm for a multilayer feed forward neural
network is over learning or over fitting. We have discussed this problem, and obtained
necessary and sufficient Experiment and conditions for over-learning problem to arise. Using
those conditions and the concept of a reproducing, this paper proposes methods for choosing
training set which is used to prevent over-learning. For a classifier, besides classification
capability, its size is another fundamental aspect. In pursuit of high performance,
many classifiers do not take into consideration their sizes and contain numerous both essential
and insignificant rules. This, however, may bring adverse situation to classifier, for its
efficiency will been put down greatly by redundant rules. Hence, it is necessary to eliminate
those unwanted rules. We have discussed various experiments with and without over learning
or over fitting problem.
KEYWORDS
Neural Network, learning, Hidden Neurons, Hidden Layers
ORIGINAL SOURCE URL : http://airccse.org/journal/ijsc/papers/2211ijsc04.pdf
http://airccse.org/journal/ijsc/current2011.html

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4. [14]S. Rajasekaran, G.A Vijayalakshmi Pai, “Neural Networks, Fuzzy Logic, and Genetic Algorithms
Synthesis and Applications” International Journal on Soft Computing (IJSC), Vol.2,No.2, May2011
51
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KDD Cup’99 Data set , http://kdd.ics.uci.edu/databases/kddcup99/kddcup99.html

5. APPLICATION OF FUZZY LOGIC IN TRANSPORT PLANNING
Amrita Sarkar1
, G.Sahoo2
and U.C.Sahoo3
1
Research Scholar, Department of Information Technology, B.I.T Mesra, Ranchi
2
Professor and Head,Department of Information Technology, B.I.T, Mesra, Ranchi
3
Assistant Professor, Department of Civil Engineerng, I.I.T, Bhabaneswar
ABSTRACT
Fuzzy logic is shown to be a very promising mathematical approach for modelling traffic and
transportation processes characterized by subjectivity, ambiguity, uncertainty and imprecision.
The basic premises of fuzzy logic systems are presented as well as a detailed analysis of fuzzy
logic systems developed to solve various traffic and transportation planning problems. Emphasis
is put on the importance of fuzzy logic systems as universal approximators in solving traffic and
transportation problems. This paper presents an analysis of the results achieved using fuzzy logic
to model complex traffic and transportation processes.
KEYWORDS
Fuzzy Logic, Transportation Planning, Mathematical modeling
ORIGINAL SOURCE URL : http://airccse.org/journal/ijsc/papers/3211ijsc01.pdf
http://airccse.org/journal/ijsc/current2012.html

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AUTHORS
Amrita Sarkar
Amrita Sarkar is a graduate Engineer in Information Technology with a post
graduation in Remote Sensing. She is presently a PhD Research Fellow at the
Department of Information Technology, Mes ra, India. She has got few research
publications in her area of specialization. Her areas of interests include Soft
Computing, Artificial Intelligence, Data Mining, DBMS and Image Processing.
Dr. G. Sahoo
Dr. G. Sahoo received his MSc in Mathematics from Utkal University in the year
1980 and PhD in the area of Computational Mathematics from Indian Institute of
Technology, Kharagpur in the year 1987. He has been associated with Birla Institute
of Technology, Mesra, Ranchi, India since 1988, and currently, he is working as a
Professor and Head in the Department of Information Technology. His r esearch
interest includes theoretical computer science, parallel and distributed computing,
evolutionary computing, information security, image processing and pattern
recognition.
Dr. U. C. Sahoo
Dr. U. C. Sahoo is working as an Assistant Professor in the Department of Civil
Engineering, Indian Institute of Technology, Bhubaneswar and is an expert in the
field of Transportation Engineering. He has more than eight years of teaching and
research experience. Presently he is engaged in re search in the area of transportation
planning, road safety and pavement engineering and published many papers in these
areas.

10. A DECISION SUPPORT SYSTEM FOR TUBERCULOSIS DIAGNOSABILITY
Navneet Walia1
, Harsukpreet Singh2
, Sharad Kumar Tiwari3
and Anurag Sharma4
1, 2, 4
Department of Electronics and Communication Engineering, CT Institute of Technology
and Research (PTU), Jalandhar
3
Department of Electrical and Instrumentation, Thapar University, Patiala
ABSTRACT
In order to cope with real-world problems more effectively, we tend to design a decision support
system for tuberculosis bacterium class identification. In this paper, we are concerned to propose
a fuzzy diagnosability approach, which takes value between {0, 1} and based on observability of
events, we formalized the construction of diagnoses that are used to perform diagnosis. In
particular, we present a framework of the fuzzy expert system; discuss the suitability of artificial
intelligence as a novel soft paradigm and reviews work from the literature for the development of
a medical diagnostic system. The newly proposed approach allows us to deal with problems of
diagnosability for both crisp and fuzzy value of input data. Accuracy analysis of designed
decision support system based on demographic data was done by comparing expert knowledge
and system generated response. This basic emblematic approach using fuzzy inference system is
presented that describes a technique to forecast the existence of bacterium and provides support
platform to pulmonary researchers in identifying the ailment effectively.
KEYWORDS
Expert system, fuzzy diagnosability, rulebased method, MATLAB, Tuberculosis (TB).
ORIGINAL SOURCE URL : http://airccse.org/journal/ijsc/papers/6315ijsc01.pdf
http://airccse.org/journal/ijsc/current2015.html

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AUTHORS
Navneet Walia is pursuing M.TECH final year in department of Electronics and
Communication Engineering at CT Institute of Technology and Research, Jalandhar.
She has done her B.TECH in trade Electronics and Communication engineering from
CEM college of Engineering and Management. She has presented many papers in
national and international conferences. Her topic of research is fuzzy logic,
neurofuzzy, genetic algorithm and its applicability to industrial sector.